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The need to identify wood by its anatomical features requires a detailed analysis of all the elements that make it up. This is a significant problem of structural wood science, the most general and complete solution of which is yet to be sought. In recent years, increasing attention has been paid to the use of computer vision methods to automate processes such as the detection, identification, and classification of different tissues and different tree species. The more successful use of these methods in wood anatomy requires a more precise and comprehensive definition of the anatomical elements, according to their geometric and topological characteristics. In this article, we conduct a detailed analysis of the limits of variation of the location and grouping of vessels in the observed microscopic samples. The present development offers criteria and quantitative indicators for defining the terms shape, location, and group of wood tissues. It is proposed to differentiate the quantitative indicators of the vessels depending on their geometric and topological characteristics. Thus, with the help of computer vision technics, it will be possible to establish topological characteristics of wood vessels, the extraction of which would be used to develop an algorithm for the automatic classification of tree species.
Nikolai Bardarov; Vladislav Todorov; Nicole Christoff. Geometric and Topological Bases of a New Classification of Wood Vascular Tissues Part 1: Shape and Arrangement Classifications of Vessels. Sustainability 2021, 13, 7545 .
AMA StyleNikolai Bardarov, Vladislav Todorov, Nicole Christoff. Geometric and Topological Bases of a New Classification of Wood Vascular Tissues Part 1: Shape and Arrangement Classifications of Vessels. Sustainability. 2021; 13 (14):7545.
Chicago/Turabian StyleNikolai Bardarov; Vladislav Todorov; Nicole Christoff. 2021. "Geometric and Topological Bases of a New Classification of Wood Vascular Tissues Part 1: Shape and Arrangement Classifications of Vessels." Sustainability 13, no. 14: 7545.
One of the challenges of planetary science is the age determination of geological units on the surface of the different planetary bodies in the solar system. This serves to establish a chronology of the geological events occurring on these different bodies, hence to understand their formation and evolution processes. An approach for dating planetary surfaces relies on the analysis of the impact crater densities with size. Approaches have been proposed to automatically detect impact craters in order to facilitate the dating process. They rely on color values from images or elevation values from Digital Elevation Models (DEM). In this article, we propose a new approach for crater detection, more specifically using their rims. The craters can be characterized by a round shape that can be used as a feature. The developed method is based on an analysis of the DEM geometry, represented as a 3D mesh, followed by curvature analysis. The classification process is done with one layer perceptron. The validation of the method is performed on DEMs of Mars, acquired by a laser altimeter aboard NASA’s Mars Global Surveyor spacecraft and combined with a database of manually identified craters. The results show that the proposed approach significantly reduces the number of false negatives compared to others based on topographic information only.
Nicole Christoff; Laurent Jorda; Sophie Viseur; Sylvain Bouley; Agata Manolova; Jean-Luc Mari. Automated Extraction of Crater Rims on 3D Meshes Combining Artificial Neural Network and Discrete Curvature Labeling. The Moon and the Planets 2020, 124, 51 -72.
AMA StyleNicole Christoff, Laurent Jorda, Sophie Viseur, Sylvain Bouley, Agata Manolova, Jean-Luc Mari. Automated Extraction of Crater Rims on 3D Meshes Combining Artificial Neural Network and Discrete Curvature Labeling. The Moon and the Planets. 2020; 124 (3-4):51-72.
Chicago/Turabian StyleNicole Christoff; Laurent Jorda; Sophie Viseur; Sylvain Bouley; Agata Manolova; Jean-Luc Mari. 2020. "Automated Extraction of Crater Rims on 3D Meshes Combining Artificial Neural Network and Discrete Curvature Labeling." The Moon and the Planets 124, no. 3-4: 51-72.
Nikolay Dandanov; Plamen Semov; Antoni Ivanov; Nicole Christoff; Vladimir Poulkov. Communication Framework for Tele-rehabilitation Systems with QoS Guarantee. MATEC Web of Conferences 2017, 125, 3008 .
AMA StyleNikolay Dandanov, Plamen Semov, Antoni Ivanov, Nicole Christoff, Vladimir Poulkov. Communication Framework for Tele-rehabilitation Systems with QoS Guarantee. MATEC Web of Conferences. 2017; 125 ():3008.
Chicago/Turabian StyleNikolay Dandanov; Plamen Semov; Antoni Ivanov; Nicole Christoff; Vladimir Poulkov. 2017. "Communication Framework for Tele-rehabilitation Systems with QoS Guarantee." MATEC Web of Conferences 125, no. : 3008.
In this paper, we propose a novel feature extraction algorithm based on curvature analysis over the 3D data and the grayscale information extracted from the images. The performance of the method is tested on 3D mesh data, provided by Mars Orbiter Laser Altimeter (MOLA) and compared to benchmark research work. The experimental results demonstrate that the proposed method can achieve better accuracy in comparison with other crater detection methods and have smaller computational complexity.
Nicole Christoff; Agata Manolova; Laurent Jorda; Jean-Luc Mari. Feature extraction and automatic detection of martian impact craters from 3D meshes. 2017 13th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS) 2017, 211 -214.
AMA StyleNicole Christoff, Agata Manolova, Laurent Jorda, Jean-Luc Mari. Feature extraction and automatic detection of martian impact craters from 3D meshes. 2017 13th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS). 2017; ():211-214.
Chicago/Turabian StyleNicole Christoff; Agata Manolova; Laurent Jorda; Jean-Luc Mari. 2017. "Feature extraction and automatic detection of martian impact craters from 3D meshes." 2017 13th International Conference on Advanced Technologies, Systems and Services in Telecommunications (TELSIKS) , no. : 211-214.